Abstract
With the rapid development of economy, customers’ demand is changing fast and customized. Therefore, how to quickly and effectively respond to the changing market demand has become one of the urgent problems for manufacturers. Job-shop is a high flexible manufacturing system that can satisfy customers’ variable demand for category of product by parallel production of multiple product paths. However, because of the complexity and dynamics, the job-shop may face a series of problems such as low production efficiency, bottlenecks and unbalanced resources. To deal with these problems, a collaborative capacity control method is proposed by integrating the customized flexibility of Reconfigurable Machine Tools (RMTs) with advanced Model Predictive Control (MPC) algorithm. Here, one new degree of freedom of RMT is adopted in the modelling of job shop manufacturing systems. Additionally, the collaborative rule between RMTs is proposed to reduce the reconfiguration frequency. Finally, the collaborative capacity control of a four-workstation job shop manufacturing system is implemented by simulation to evaluate the effectiveness of the proposed method.
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